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Integrating ethical practices into the AI development process for artificialintelligence (AI) is essential to ensure safe, fair, and responsible operation.AI ethics involves applying ethical principles to the entire life cycle of AIsystems. This is essential to mitigate potential risks and harms associatedwith AI, such as algorithm biases. To achieve this goal, responsible designpatterns (RDPs) are critical for Machine Learning (ML) pipelines to guaranteeethical and fair outcomes. In this paper, we propose a comprehensive frameworkincorporating RDPs into ML pipelines to mitigate risks and ensure the ethicaldevelopment of AI systems. Our framework comprises new responsible AI designpatterns for ML pipelines identified through a survey of AI ethics and datamanagement experts and validated through real-world scenarios with expertfeedback. The framework guides AI developers, data scientists, andpolicy-makers to implement ethical practices in AI development and deployresponsible AI systems in production.

Responsible Design Patterns for Machine Learning Pipelines